The Crossfire transmitter perturbs the usual functioning on HDZero & Avatar HD FPV Goggles. If you get closer to the goggles’ power cable or goggle, the goggle will shut down or reboot. This video presents two solutions to solve this issue.

00:00 – Video starts.
00:07 – The problem (Crossfire emission power 250 mW)
00:35 – The problem (Crossfire emission power 500 mW)
01:08 – First approach: using a ferrite cable clip.
03:07 – Second approach: using a capacitor as a low-pass filter.
04:27 – Conclusions.

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║╚╣║║║╚╣╚╣╔╣╔╣║╚╣═╣ → http://bit.ly/3arWvOq.
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Nearly three decades later, the Apache’s status as the world’s premier attack helicopter remains largely unchallenged.

Here’s What You Need to Remember: The latest AH-64E Guardian model boasts uprated engines, remote drone-control capabilities, and a sensors designed to highlight muzzle flashes on the battlefield below. The Army has also experimentally deployed Apaches on U.S. Navy ships and had them practice anti-ship missions, and even tested a laser-armed Apache.

Early in the morning of January 17, 1991, eight sleek helicopters bristling with missiles swooped low over the sands of the An Nafud desert in as they soared towards the border separating Saudi Arabia from Iraq.

NASA will begin a new RS-25 test series Oct. 5, the final round of certification testing ahead of production of an updated set of the engines for the SLS (Space Launch System) rocket. The engines will help power future Artemis missions to the Moon and beyond.

A series of 12 tests stretching into 2024 is scheduled to occur on the Fred Haise Test Stand at NASA’s Stennis Space Center near Bay St. Louis, Mississippi. The tests are a key step for lead SLS engines contractor Aerojet Rocketdyne, an L3Harris Technologies company, to produce engines that will help power the SLS rocket, beginning with Artemis V.

“NASA and our industry partners continue to make steady progress toward restarting production of the RS-25 engines for the first time since the space shuttle era as we prepare for our more ambitious missions to deep space under Artemis with the SLS rocket,” said Johnny Heflin, liquid engines manager for SLS at NASA’s Marshall Space Flight Center in Huntsville, Alabama. “The upcoming fall test series builds off previous hot fire testing already conducted at NASA Stennis to help certify a new design that will make this storied spaceflight engine even more powerful.”

The 2023 Nobel Prize in Chemistry was awarded to three scientists who discovered and developed quantum dots, which are very small particles that can change color depending on their size. Quantum dots are tiny particles of a special kind of material called a semiconductor. They are so small that they behave differently from normal materials. They can absorb and emit light of different colors depending on their size and shape.

You can think of quantum dots as artificial atoms that can be made in a lab! They have some of the same properties as atoms, such as having discrete energy levels (meaning they can only exist in certain distinct energy states, and they cannot have energy values between these specific levels) and being able to form molecules with other quantum dots. But they also have some unique features that make them useful for many applications, such as displays, solar cells, sensors, and medicine, which I shall discuss later in this story!

To grasp the workings of quantum dots, a bit of quantum mechanics knowledge comes in handy. Quantum mechanics teaches us that these tiny entities can possess only specific amounts of energy, and they transition between these energy levels by absorbing or emitting light. The energy of this light is determined by the difference in energy levels. In typical materials like metals or plastics, energy levels are closely packed, forming continuous bands where electrons can move freely, resulting in less specific light absorption or emission. However, in semiconductors like silicon or cadmium selenide, there’s a gap between these bands known as the “band gap.” Electrons can only jump from one band to another by interacting with light having an energy level that precisely matches the band gap, making semiconductors valuable for creating devices like transistors and LEDs.

Skydio X10 autonomous drones deliver the best sensors for a drone this small, piloted by the most advanced AI in the sky.

Ben Dixon, a researcher in the Optical and Quantum Communications Technology Group, explains how the process works: “First, you need to generate pairs of specific entangled qubits (called Bell states) and transmit them in different directions across the network link to two separate quantum repeaters, which capture and store these qubits. One of the quantum repeaters then does a two-qubit measurement between the transmitted and stored qubit and an arbitrary qubit that we want to send across the link in order to interconnect the remote quantum systems. The measurement results are communicated to the quantum repeater at the other end of the link; the repeater uses these results to turn the stored Bell state qubit into the arbitrary qubit. Lastly, the repeater can send the arbitrary qubit into the quantum system, thereby linking the two remote quantum systems.”

To retain the entangled states, the quantum repeater needs a way to store them — in essence, a memory. In 2020, collaborators at Harvard University demonstrated holding a qubit in a single silicon atom (trapped between two empty spaces left behind by removing two carbon atoms) in diamond. This silicon “vacancy” center in diamond is an attractive quantum memory option. Like other individual electrons, the outermost (valence) electron on the silicon atom can point either up or down, similar to a bar magnet with north and south poles. The direction that the electron points is known as its spin, and the two possible spin states, spin up or spin down, are akin to the ones and zeros used by computers to represent, process, and store information. Moreover, silicon’s valence electron can be manipulated with visible light to transfer and store a photonic qubit in the electron spin state. The Harvard researchers did exactly this; they patterned an optical waveguide (a structure that guides light in a desired direction) surrounded by a nanophotonic optical cavity to have a photon strongly interact with the silicon atom and impart its quantum state onto that atom. Collaborators at MIT then showed this basic functionality could work with multiple waveguides; they patterned eight waveguides and successfully generated silicon vacancies inside them all.

Lincoln Laboratory has since been applying quantum engineering to create a quantum memory module equipped with additional capabilities to operate as a quantum repeater. This engineering effort includes on-site custom diamond growth (with the Quantum Information and Integrated Nanosystems Group); the development of a scalable silicon-nanophotonics interposer (a chip that merges photonic and electronic functionalities) to control the silicon-vacancy qubit; and integration and packaging of the components into a system that can be cooled to the cryogenic temperatures needed for long-term memory storage. The current system has two memory modules, each capable of holding eight optical qubits.

Of all the holy grails in robotics, learning may well be the holiest. In an era when the term “general purpose” is tossed around with great abandon, however, it can be difficult for non-roboticists to understand what today’s systems can — and can’t — do. The truth of it is that most robots these days are built to do one (or a couple, if you’re lucky) thing really well.

It’s a truth that spans the industry, from the lowliest robot vacuum to the most advanced industrial system. So, how do we make the transition from single to general purpose robotics? Certainly, there are going to be a lot of stops in multipurpose land along the way.

The answer is, of course, robot learning. Walk into nearly any robotics research lab these days and you will find teams working on tackling the issue. The same applies to startups and corporations, as well. Look at companies Viam and Intrinsic, which are working to lower the bar of entry for robot programming.

The latest research on quantum materials and electron curves could revamp our energy-efficient electronics.